A Location-based Runs-and-gaps Model for Predicting Tcp Performance over a Uav Wireless Channel

In this paper, we use a location-based model to predict the performance of the Transmission Control Protocol (TCP) over a varying wireless channel between a UAV and ground nodes. As a UAV traverses its flight path, the wireless channel may experience periods of significant packet loss, successful packet delivery, and intermittent reception. By capturing packet run-length and gap-length statistics at various locations on the flight path, the model can predict TCP throughput in spite of dynamically changing channel characteristics. We train the model by using packet traces obtained from flight tests in the field and validate it by comparing TCP throughput distributions for model-generated traces against those for actual traces randomly sampled from field data.